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Towards Merkle Trees for High-Performance Data Systems

El-Hindi, Muhammad ; Ziegler, Tobias ; Binnig, Carsten (2023)
Towards Merkle Trees for High-Performance Data Systems.
1st Workshop on Verifiable Database Systems (VDBS 2023). Seattle, USA (23.06.2023-23.06.2023)
doi: 10.1145/3595647.3595651
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Merkle Trees (and its variants) are widely used for building secure outsourced data systems. The adoption of Merkle Trees for high-performance data systems, however, uncovered major performance challenges. First and unlike classical data structures, Merkle Trees involve expensive cryptographic operations and are thus CPU-bound. Second, they are not well suited for modern multi-core CPUs because they introduce a single point of contention making Merkle Trees hard to parallelize. While recent work aimed at replacing Merkle Trees to circumvent their performance problem, we suggest new techniques to speed-up this ubiquitous data structure and achieve high-performance. In this paper, we present initial results showing that in contrast to common wisdom it is indeed possible to build high-performance Merkle Trees with orders of magnitude performance improvements.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2023
Autor(en): El-Hindi, Muhammad ; Ziegler, Tobias ; Binnig, Carsten
Art des Eintrags: Bibliographie
Titel: Towards Merkle Trees for High-Performance Data Systems
Sprache: Englisch
Publikationsjahr: 23 Juni 2023
Verlag: ACM
Buchtitel: VDBS '23: Proceedings of the 1st Workshop on Verifiable Database Systems
Veranstaltungstitel: 1st Workshop on Verifiable Database Systems (VDBS 2023)
Veranstaltungsort: Seattle, USA
Veranstaltungsdatum: 23.06.2023-23.06.2023
DOI: 10.1145/3595647.3595651
Kurzbeschreibung (Abstract):

Merkle Trees (and its variants) are widely used for building secure outsourced data systems. The adoption of Merkle Trees for high-performance data systems, however, uncovered major performance challenges. First and unlike classical data structures, Merkle Trees involve expensive cryptographic operations and are thus CPU-bound. Second, they are not well suited for modern multi-core CPUs because they introduce a single point of contention making Merkle Trees hard to parallelize. While recent work aimed at replacing Merkle Trees to circumvent their performance problem, we suggest new techniques to speed-up this ubiquitous data structure and achieve high-performance. In this paper, we present initial results showing that in contrast to common wisdom it is indeed possible to build high-performance Merkle Trees with orders of magnitude performance improvements.

Freie Schlagworte: Outsourced Databases, Merkle Trees, Verifiable Databases, Concurrency
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Data and AI Systems
Hinterlegungsdatum: 07 Nov 2023 10:12
Letzte Änderung: 27 Nov 2023 12:37
PPN: 513494219
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